Abstract We adapt the Douglas–Rachford (DR) splitting method to solve nonconvex
feasibility problems by studying this method for a class of nonconvex optimization problem …

Abstract The Douglas–Rachford splitting algorithm is a classical optimization method that
has found many applications. When specialized to two normal cone operators, it yields an …

We consider the recovery of a finite stream of Dirac pulses at nonuniform locations, from
noisy lowpass-filtered samples. We show that maximum-likelihood estimation of the …

Abstract The Douglas–Rachford algorithm is a very popular splitting technique for finding a
zero of the sum of two maximally monotone operators. The behaviour of the algorithm …

The alternating direction multiplier method (ADMM) is widely used in computer graphics for
solving optimization problems that can be nonsmooth and nonconvex. It converges quickly …

Abstract The Douglas–Rachford algorithm is an optimization method that can be used for
solving feasibility problems. To apply the method, it is necessary that the problem at hand is …

The Douglas–Rachford method is a splitting method frequently employed for finding zeros of
sums of maximally monotone operators. When the operators in question are normal cone …

The Douglas–Rachford (DR) method is a widely used method for finding a point in the
intersection of two closed convex sets (feasibility problem). However, the method converges …

In this paper, we establish sublinear and linear convergence of fixed point iterations
generated by averaged operators in a Hilbert space. Our results are achieved under a …

In this paper, we present two Douglas–Rachford inspired iteration schemes which can be
applied directly to N-set convex feasibility problems in Hilbert space. Our main results are …